Hardening-softening of Al0.3CoCrFeNi high-entropy alloy under nanoindentation

Guo, Qianqian; Hou, Hua; Pan, Yonglong; Pei, Xiaolong; Song, Zhiyong; Liaw, Peter K.; Zhao, Yuhong

doi:10.1016/j.matdes.2023.112050

Cited by 86 publications

(23 citation statements)

References 43 publications

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“…Whereas, the corresponding dislocation densities at the same indentation depth and indenter radii are observed as 2.12 × 10 15 m 2 , 5.48 × 10 15 m 2 , 8.46 × 10 15 m 2 , 1.17 × 10 16 m 2 . The similar magnitude of dislocation densities is reported by Guo et al [47]. Notably, the release of independent PDL can only be observed for the indenter radius of 4 nm at an indentation depth of 1 nm.…”

Section: Influence Of Indenter Sizesupporting

confidence: 88%

“…This process contributes to the development of embryonic PDL, followed by the subsequent formation of independent PDL. A good amount of previous studies reported the mechanism behind the formation of PDL in different material systems under nanoindentation simulation [47,48,53]. In the process of elastic deformation, the initial structural transformation occurs at an indentation depth of 0.3 nm, marked by the nucleation of SFs enclosed by Shockley partial dislocations (1/6<112>), as illustrated in the inset of figure 2(d).…”

Section: 11mentioning

confidence: 95%

“…Likewise, Muthupandi et al [46] investigated the deformation behaviour of AlCoCrFeNi HEA under nanoindentation and revealed the pileup phenomenon attributed to the activated dislocations in the vicinity of the indentation zone. Similarly, Guo et al [47] conducted the nanoindentation of Al 0.3 CoCrFeNi HEA in an MD simulation environment and observed the increase in indentation resistance as a consequence of dislocation multiplication and cross-slip, which leads to work hardening. On the contrary, a study conducted by Wang et al [48] demonstrated the mechanism of plastic deformation in Al 0.3 CoCrFeNi HEA which consists of generation and propagation of different dislocation types such as Shockley partial, stacking faults (SFs), and prismatic dislocation loops (PDLs) in response to action and reaction among the dislocations.…”

Section: Introductionmentioning

confidence: 99%

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Enhancing mechanical performance of Al_0.3CoCrFeNi HEA films through graphene coating: insights from nanoindentation and dislocation mechanism analysis

Barman,

Gupta,

Dey

2024

Modelling Simul. Mater. Sci. Eng.

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The present study comprehensively elucidates the nanoindentation response of graphene-coated Al0.3CoCrFeNi high-entropy alloy (HEA), by investigating the underlying mechanism of dislocation nucleation and propagation on the atomic level. In this regard, a series of molecular dynamics (MD) simulation of nano-indentation is performed over various configurations of pristine and graphene coated Al0.3CoCrFeNi HEA substrates. To begin with, the MD simulation-derived Young's modulus (158.74 GPa) and hardness (13.75 GPa) of the Al0.3CoCrFeNi HEA is validated against the existing literature to establish the credibility of the utilized simulation method. The post-indentation deformation mechanism of pristine Al0.3CoCrFeNi HEA is further investigated by varying substrate size, indenter size, and indentation rate, and the materials behaviour is evaluated based on functional responses such as Young's modulus, hardness, and dislocation density, etc. In the following stage, graphene coated Al0.3CoCrFeNi HEA is nano-indented, resulting in much greater indentation forces compared to pure HEA substrates, indicating higher surface hardness (two-fold increase when compared to pristine HEA). The underlying deformation mechanism demonstrated that inducing graphene coating results in increased dislocation density and a more extensive, entangled dislocation network within the HEA substrate, which leads to strain-hardening. The combination of increased hardness, enhanced strain hardening, and prevention of pile-up effects suggests that Gr-coated HEA substrates have the potential to serve as surface-strengthening materials. The scientific contribution of this study involves extensively unveiling the deformation mechanism of graphene coated Al0.3CoCrFeNi HEA substrate on the atomic scale, which will pave the way for a bottom-up approach to developing graphene coated engineered surfaces.

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Section: Influence Of Indenter Sizesupporting

confidence: 88%

Section: 11mentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

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Enhancing mechanical performance of Al_0.3CoCrFeNi HEA films through graphene coating: insights from nanoindentation and dislocation mechanism analysis

Barman,

Gupta,

Dey

2024

Modelling Simul. Mater. Sci. Eng.

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“…When the laser beam coincides with the substrate surface, a portion of it is absorbed by the powder elements and substrate, resulting in melt pool formation (Yang et al , 2023; Zhang et al , 2022d; Zhang et al , 2023). Three powder jets combine to form a single conical stream of powder particles fed directly into the melt pool created by the high-power focused laser spot, resulting in layer formation (Guo et al , 2023; Tian et al , 2022; Wang et al , 2020). This process continues until the 3D computer-aided design (CAD) model is printed in a 3D physical object.…”

Section: Analytical Modellingmentioning

confidence: 99%

Printed layers height calibration curve and porosity in laser melting deposition of Ti6Al4V combining experiments, mathematical modelling and deep neural network

Mahmood,

Diana,

Sajjad

et al. 2023

RPJ

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Purpose Porosity is a commonly analyzed defect in the laser-based additive manufacturing processes owing to the enormous thermal gradient caused by repeated melting and solidification. Currently, the porosity estimation is limited to powder bed fusion. The porosity estimation needs to be explored in the laser melting deposition (LMD) process, particularly analytical models that provide cost- and time-effective solutions compared to finite element analysis. For this purpose, this study aims to formulate two mathematical models for deposited layer dimensions and corresponding porosity in the LMD process. Design/methodology/approach In this study, analytical models have been proposed. Initially, deposited layer dimensions, including layer height, width and depth, were calculated based on the operating parameters. These outputs were introduced in the second model to estimate the part porosity. The models were validated with experimental data for Ti6Al4V depositions on Ti6Al4V substrate. A calibration curve (CC) was also developed for Ti6Al4V material and characterized using X-ray computed tomography. The models were also validated with the experimental results adopted from literature. The validated models were linked with the deep neural network (DNN) for its training and testing using a total of 6,703 computations with 1,500 iterations. Here, laser power, laser scanning speed and powder feeding rate were selected inputs, whereas porosity was set as an output. Findings The computations indicate that owing to the simultaneous inclusion of powder particulates, the powder elements use a substantial percentage of the laser beam energy for their melting, resulting in laser beam energy attenuation and reducing thermal value at the substrate. The primary operating parameters are directly correlated with the number of layers and total height in CC. Through X-ray computed tomography analyses, the number of layers showed a straightforward correlation with mean sphericity, while a converse relation was identified with the number, mean volume and mean diameter of pores. DNN and analytical models showed 2%–3% and 7%–9% mean absolute deviations, respectively, compared to the experimental results. Originality/value This research provides a unique solution for LMD porosity estimation by linking the developed analytical computational models with artificial neural networking. The presented framework predicts the porosity in the LMD-ed parts efficiently.

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“…Therefore, numerous investigations are carried out to boost the magnetic properties of M-type hexaferrites to fulfill the market requirements. Various techniques may be used to extend the characteristics of M-type hexaferrites, one of which is the induction of dopant elements [21][22][23]. The choice of dopant metal significantly influences M-type hexa-ferrite's aspects.…”

Section: Introductionmentioning

confidence: 99%

Effect of ferromagnetic cobalt on characteristics of coercive Aluminium substituted BaFe_11.5Al_0.5O₁₉ hexaferrites

Ijaz,

Asif,

El-Zahhar

et al. 2023

Phys. Scr.

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Magnetic and structural characteristics of M-type barium hexaferrite nanoparticles can be tuned by doping different di or trivalent metal ions. Here BaFe11.5-xAl0.5CoxO19 hexaferrite nanoparticles were synthesized using a sol-gel process, and the influence of doping concentrations on M-type BaFe11.5-xAl0.5CoxO19 hexaferrite nanoparticles was deliberated. The XRD analysis confirms the formation of ferrites successfully. When the doping level increased, the grain dimension (D) initially reduced and then increased. Similarly, the lattice constants ‘a’ and ‘c’ decreased initially and then increased. The findings indicated that the (Mr/Ms) ratio decreased initially as the doping content increased, but at higher doping ranges, it started to rise. At the same time, coercivity (Hc) and magneto-crystalline an-isotropy field (Ha) increased as the doping level increased. Excellent magnetic characteristics were obtained for BaFe11.5-xAl0.5CoxO19 hexaferrites at doping content of (x=1.5), with magnetic moment 10.80µB, saturation magnetization 57.35 emu/g, and coercivity 5.21 kOe along anisotropic applied field of 1.62 kOe. The findings mentioned above imply that magnetic characteristics of M-type Barium hexaferrites can be significantly improved upon doping of Cobalt against Aluminium substituted hexaferrite, which will make such types of Ba-hexaferrite very useful in many applications, for example, in magnetic filters, memory devices, and recording media, etc.

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Hardening-softening of Al0.3CoCrFeNi high-entropy alloy under nanoindentation

Cited by 86 publications

References 43 publications

Enhancing mechanical performance of Al_0.3CoCrFeNi HEA films through graphene coating: insights from nanoindentation and dislocation mechanism analysis

Enhancing mechanical performance of Al_0.3CoCrFeNi HEA films through graphene coating: insights from nanoindentation and dislocation mechanism analysis

Printed layers height calibration curve and porosity in laser melting deposition of Ti6Al4V combining experiments, mathematical modelling and deep neural network

Effect of ferromagnetic cobalt on characteristics of coercive Aluminium substituted BaFe_11.5Al_0.5O₁₉ hexaferrites

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Hardening-softening of Al0.3CoCrFeNi high-entropy alloy under nanoindentation

Cited by 86 publications

References 43 publications

Enhancing mechanical performance of Al0.3CoCrFeNi HEA films through graphene coating: insights from nanoindentation and dislocation mechanism analysis

Enhancing mechanical performance of Al0.3CoCrFeNi HEA films through graphene coating: insights from nanoindentation and dislocation mechanism analysis

Printed layers height calibration curve and porosity in laser melting deposition of Ti6Al4V combining experiments, mathematical modelling and deep neural network

Effect of ferromagnetic cobalt on characteristics of coercive Aluminium substituted BaFe11.5Al0.5O19 hexaferrites

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Product

Resources

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Enhancing mechanical performance of Al_0.3CoCrFeNi HEA films through graphene coating: insights from nanoindentation and dislocation mechanism analysis

Enhancing mechanical performance of Al_0.3CoCrFeNi HEA films through graphene coating: insights from nanoindentation and dislocation mechanism analysis

Effect of ferromagnetic cobalt on characteristics of coercive Aluminium substituted BaFe_11.5Al_0.5O₁₉ hexaferrites